#### Filter Results:

- Full text PDF available (6)

#### Publication Year

2004

2006

- This year (0)
- Last 5 years (0)
- Last 10 years (0)

#### Publication Type

#### Co-author

#### Journals and Conferences

#### Key Phrases

Learn More

- M. Schuermans, Philippe Lemmerling, Sabine Van Huffel
- Numerical Lin. Alg. with Applic.
- 2004

dictive computer models for medical classification problems using patient data and expert knowledge), several PhD/postdoc & fellow grants; Flemish Government: FWO: PhD/postdoc grants, projects, G.0200.00 (damage detection in composites by optical fibers), G. SUMMARY This paper extends the Weighted Low Rank Approximation (WLRA) approach towards linearly… (More)

- M. Schuermans, Philippe Lemmerling, Lieven De Lathauwer, Sabine Van Huffel
- Signal Processing
- 2006

In this paper we discuss the problem of recovering the vertices of a planar polygon from its measured complex moments. Because the given, measured moments can be noisy, the recovered vertices are only estimates of the true ones. The literature offers many algorithms for solving such an estimation problem. We will restrict our discussion to the Total Least… (More)

- M. Schuermans, Philippe Lemmerling, Sabine Van Huffel
- Numerical Lin. Alg. with Applic.
- 2006

This paper extends the Weighted Low Rank Approximation (WLRA) approach towards linearly structured matrices. In the case of Hankel matrices with a special block structure an equivalent unconstrained optimization problem is derived and an algorithm for solving it is proposed.

The Maximum Likelihood PCA (MLPCA) method has been devised in chemometrics as a generalization of the well-known PCA method in order to derive consistent estimators in the presence of errors with known error distribution. For similar reasons, the Total Least Squares (TLS) method has been generalized in the field of computational mathematics and engineering… (More)

In order to find more sophisticated trends in data, potential correlations between larger and larger groups of variables must be considered. Unfortunately, the number of such correlations generally increases exponentially with the number of input variables and, as a result, brute force approaches become unfeasible. So, the data needs to be simplified… (More)

An algorithm that transforms symmetric matrices into similar semiseparable ones has been proposed recently. Similarly to the Householder reduction, the latter algorithm works without taking into account the structure of the original matrix. In this paper we propose a Lanczos–like algorithm to transform a symmetric matrix into a similar semiseparable one… (More)

- ‹
- 1
- ›